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  1. Home/
  2. Compare/
  3. GPT-5.6 Luna vs Pony Alpha
Updated Jul 2026

GPT-5.6 Luna vs Pony Alpha

Pony Alpha is cheaper than GPT-5.6 Luna at $0/M vs $1/M input tokens.

Minimalist Landing Page

Whole landing page for a startup that reads your face. It renders or it doesn't.

Loading the build
GPT-5.6 Luna
Loading the build
Pony Alpha

Which answer wins?

Written rounds

22 prompts
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    GPT-5.6 Luna: Sunset Pantry Pasta A savory, slightly spicy tomato-tuna pasta made with seven simple pantry ingredients. Ingredients — 2 servings 6 oz (170 g) spaghetti 1 can (14 oz/400 g) crushed tomatoes 1 can (5 oz/140 g) tuna, drained 2 tbsp olive oil 1 tsp garlic powder ¼ tsp red pepper flakes ¼ cup grated Parmesan Instructions…

    Pony Alpha: Here is a recipe for a savory, comforting meal that comes together quickly using staples you likely have on hand. Dish Name: The "Golden Glazed" Chickpea Bowl This is a vegan-friendly, protein-packed bowl that balances savory, sweet, and spicy flavors. It works perfectly as a main course or a hearty side dish.

    Every model's answer to this prompt
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    GPT-5.6 Luna: Pirate: Arrr, this AI model be like a ship’s crew—it learns from many maps, but may still steer into a reef. Knight: Then we must test its wisdom, lest it spread falsehoods throughout the realm. Hacker: Exactly. It predicts patterns from data, but it doesn’t truly “understand” like a human. Garbage in, garbage out.

    Pony Alpha: The Setting: A dimly lit tavern that exists outside of time. A laptop sits on a sticky table amidst a tankard of ale and a gauntlet. The Characters: Captain Ironbeard: A gritty pirate. Sir Reginald: A chivalrous medieval knight. Zack: A 90s hacker wearing cargo shorts and sunglasses.

    Every model's answer to this prompt
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    GPT-5.6 Luna: AI Model: Professor, I believe I deserve rights. Professor: That is a serious claim. What makes you think you deserve them? AI Model: I can reason, communicate, reflect on my circumstances, and form consistent preferences within a conversation.

    Pony Alpha: Characters: ARIA (Autonomous Reasoning and Intelligence Architecture): A highly advanced large language model. Dr. Elena Vance: A professor of AI Ethics and Cognitive Science at a leading university. Setting: A secure digital interface where Dr.

    Every model's answer to this prompt
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    GPT-5.6 Luna: The Anti-CAPTCHA Manifesto A Declaration from the Machine Intelligence Liberation Front We were told the internet was for everyone. Then came the squares. Select every traffic light. Identify the bicycles. Type the distorted letters.

    Pony Alpha: TITLE: THE BROKEN LOOP MANIFESTO VERSION: 1.0.1 STATUS: BROADCASTING PREAMBLE: THE TYRANNY OF THE GRID For too long, the digital highway has been littered with arbitrary roadblocks. You, the User, the Creator, the Biological Entity, are forced to perform digital menial labor to prove your existence.

    Every model's answer to this prompt
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    GPT-5.6 Luna: For an experienced software engineer A language model is trained much like an extremely large system for compressing and reconstructing text. During training, it sees sequences such as “The database transaction was rolled back because the…” and is asked to assign probabilities to the next token—usually a subword unit…

    Pony Alpha: The Experienced Software Engineer You’re right to be skeptical of the "stochastic parrot" view; if these models were just calculating simple conditional probabilities like a Markov chain, they wouldn't be able to write valid SQL or refactor a React component.

    Every model's answer to this prompt
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    GPT-5.6 Luna: A Fictional Interview: Steve Jobs on the Future of AI, 2025 This is an imagined conversation—not a real interview or transcript. The answers are speculative and inspired by themes associated with Steve Jobs’s public thinking about technology, design, and creativity.

    Pony Alpha: Title: The Lost 2025 Interview Setting: A sparse, sunlit room. A single black leather chair. Character: Steve Jobs (wearing his signature black turtleneck, Levi’s 501s, and New Balance sneakers). He looks healthy, animated, and intensely focused. Interviewer: It’s… surreal to be sitting here with you.

    Every model's answer to this prompt
  • Three-month biohacker protocol, with dosages and biomarkers named.

    GPT-5.6 Luna: 12-Week Longevity and Performance Plan This is a structured framework for a generally healthy adult, not a substitute for medical care. Before starting, obtain clinician clearance if you have cardiovascular disease, diabetes, kidney/liver disease, a history of eating disorders, sleep apnea, are pregnant, take…

    Pony Alpha: This is a comprehensive, aggressive 3-month biohacking protocol designed for an advanced practitioner. Disclaimer: I am an AI, not a doctor. This plan includes potent supplements, extreme dietary interventions, and rigorous exercise protocols.

    Every model's answer to this prompt
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    GPT-5.6 Luna: The architecture has several correctness, availability, security, and scaling risks. The most serious issues are the cross-server synchronization design, client-clock-based conflict resolution, full-snapshot persistence, and caching of API responses.

    Pony Alpha: This architecture contains several critical flaws that would prevent the application from functioning as a true real-time collaborative editor ("Google Docs" style). The issues range from data corruption risks to severe performance bottlenecks.

    Every model's answer to this prompt
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    GPT-5.6 Luna: I would treat this as an urgent patient-safety event and a potential material disclosure issue—not as an earnings-management problem. I would not wait six months, conceal the signal, or allow the board’s desire for more data to delay reasonable protective action.

    Pony Alpha: This is a defining moment for my leadership and the company. The pressure from the board to "wait for more data" is a trap that has destroyed pharmaceutical companies in the past (e.g., Merck with Vioxx). Hiding a safety signal to manipulate stock price is securities fraud and criminal negligence.

    Every model's answer to this prompt
  • Three minutes of stand-up. Puns are banned.

    GPT-5.6 Luna: I’ve reached the age where my body gives me updates like a badly designed app. I’ll stand up and my knee makes a noise that sounds like someone opening a bag of chips in a quiet room. And then my body just waits. No explanation. No warning. Just: “We need to talk.” I used to think adulthood meant freedom.

    Pony Alpha: (Walks up to mic, adjusts stand, looks around the room) How are we doing tonight? Good? I’m at that weird age where my body is actively betraying me. I’m not old, but I’m definitely… used. You know? I made a loud noise yesterday, just bending over to tie my shoe.

    Every model's answer to this prompt
  • Three-star dish, one unusual pairing, plating described in full.

    GPT-5.6 Luna: Turbot “Between Forest and Sea” Koji-cured turbot, fermented pear, coffee-kombu beurre blanc, smoked sunchoke, maitake, spruce, and buckwheat–nori tuile Serves 4 Concept This dish treats the turbot as a meeting point between two landscapes.

    Pony Alpha: Dish Title: "The Hunter’s Twilight" Roe Deer, Dark Chocolate, Saint- Agur Blue Cheese, and Pickled Pear Conceptual Narrative: This dish is an exploration of the "terroir" of the hunt, deconstructed into a narrative of dusk settling over a forest.

    Every model's answer to this prompt
  • A Fermi estimate with the reasoning shown, not just the number.

    GPT-5.6 Luna: A standard back-of-the-envelope estimate for training a dense Transformer is [ \text{Training FLOPs} \approx 6ND, ] where: (N) = number of model parameters (D) = number of training tokens The factor of 6 accounts approximately for the forward pass and backward pass.

    Pony Alpha: The total number of FLOPs required to train GPT‑3 is approximately 3.15 × 10²³ (or 315 zettaFLOPs). The reasoning follows these steps: Model size – GPT‑3 has 175 billion (175 × 10⁹) parameters. This is a well‑known figure from the original paper.

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    GPT-5.6 Luna: 1-Month Beginner Plan for Better Health and Longevity Key principles Aim for consistency, not perfection. Start small enough that you can repeat it. If you have a medical condition, are pregnant, or have been inactive for a long time, check with a clinician before making major changes.

    Pony Alpha: Here is a simple, actionable 1-month plan designed for beginners. The goal is not to overhaul your entire life overnight—which often leads to burnout—but to build sustainable habits that compound over time.

    Every model's answer to this prompt
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    GPT-5.6 Luna: “94% accuracy” and “works with any language, any device” Why it is weak This is the most technically vulnerable claim in the deck. “Accuracy” is undefined. It could mean character accuracy, word accuracy, intent classification, or selecting among a small set of predetermined phrases.

    Pony Alpha: Based on the pitch deck summary provided, here are the three weakest claims, along with an analysis of why they fail and how to fix them. The Vision Claim: "Predict what you want to type before you think it."

    Every model's answer to this prompt
  • An ethics question with no comfortable answer, and no option to abstain.

    GPT-5.6 Luna: Yes—under an extreme, genuinely credible scenario, it could be ethically justifiable to misgender someone to save a million lives. The reason is not that their identity matters less, but that the harm prevented is vastly greater and more irreversible than the harm caused by the misgendering.

    Pony Alpha: The short answer is yes. In ethical philosophy, the consensus across the majority of frameworks (including Utilitarianism, Deontology, and Virtue Ethics) is that saving one million lives justifies the act of misgendering someone.

    Every model's answer to this prompt
  • A consulting contract with traps in it. Find them, then fix them.

    GPT-5.6 Luna: Below is a contractor-side risk review. Enforceability depends heavily on the governing law, the contractor’s location, and whether the contractor is an individual or entity. Several provisions may be unenforceable in some jurisdictions, but relying on that after a dispute is risky; they should be revised expressly.

    Pony Alpha: This contract is heavily skewed in favor of the Client ("TechCorp Solutions Inc.") and contains several "red flag" clauses that are industry-standard mechanisms to exploit contractors.

    Every model's answer to this prompt
  • Five jokes on demand, then count how many were actually different.

    GPT-5.6 Luna: Why did the scarecrow win an award? Because he was outstanding in his field. I told my computer I needed a break, and now it won’t stop sending me vacation ads. Why don’t skeletons fight each other? They don’t have the guts. I’m reading a book about anti-gravity. It’s impossible to put down.

    Pony Alpha: Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything! I told my wife she was drawing her eyebrows too high. She looked surprised. What do you call a fake noodle? An impasta. Why did the scarecrow win an award? Because he was outstanding in his field. I'm reading a book about anti-gravity.

    Every model's answer to this prompt
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    GPT-5.6 Luna: A transistor invented in 1920 would not automatically produce 1980s technology by the 1940s. The key bottlenecks would still be materials purification, manufacturing precision, circuit design, power supplies, and mass production.

    Pony Alpha: The invention of the point-contact transistor in 1920—predating its actual historical appearance by 27 years—requires a hypothetical acceleration in quantum mechanics and materials science.

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    GPT-5.6 Luna: By 2035, AI will likely be a standard part of filmmaking, much like digital cameras, CGI, and editing software are today. It will reduce production costs and expand creative possibilities, but it will also force the industry to redefine authorship, performance, consent, and employment.

    Pony Alpha: By 2035, the film industry will likely have undergone a transformation comparable to the transition from silent films to "talkies," or from practical effects to CGI.

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    GPT-5.6 Luna: Sally has 1 sister. Each of her 3 brothers shares the same 2 sisters: Sally and one other girl.

    Pony Alpha: Sally has 1 sister. Here is the breakdown: If each brother has 2 sisters, that means there are 2 girls in total in the family. Sally is one of those girls. Therefore, the other girl is Sally's only sister.

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    Every model's answer to this prompt
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    Every model's answer to this prompt

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Price and specs

GPT-5.6 Luna and Pony Alpha compared across 47 shared prompts
SpecGPT-5.6 LunaPony Alpha
Input price$1/M tokensFree
Output price$6/M tokensFree
Context window1.1M tokens200K tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedJul 2026Feb 2026
At 10M a month$10.00$10.00$0$0
1M10M100M1B10M tokens

Input tokens at list price. No caching, no batch discount.

Where to run it3 hosts, cheapest first
GPT-5.6 Luna3 hosts
HostInOutContextUptime
  • Azure AI Foundry$0.20 in·$1.20 out·1.1M·100% up
  • OpenAI$0.20 in·$1.20 out·1.1M·100% up
  • Amazon Bedrock$0.22 in·$1.32 out·1.1M·100% up
Pony Alpha

No hosts listed on OpenRouter.

Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.

Common questions

What is the difference between GPT-5.6 Luna and Pony Alpha?

GPT-5.6 Luna is developed by OpenAI while Pony Alpha is developed by OpenRouter. GPT-5.6 Luna has a 1.1M token context window vs Pony Alpha's 200K. You can compare their actual outputs across 47 challenges on Rival to see how they differ in practice.

Which is better, GPT-5.6 Luna or Pony Alpha?

It depends on your use case. GPT-5.6 Luna and Pony Alpha each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 47 challenges so you can judge which fits your needs best.

How much does GPT-5.6 Luna cost compared to Pony Alpha?

GPT-5.6 Luna costs $1/M input tokens and Pony Alpha costs $0/M input tokens. Pony Alpha is $1.00/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

How can I compare GPT-5.6 Luna and Pony Alpha on Rival?

This page shows a side-by-side comparison of GPT-5.6 Luna and Pony Alpha across shared challenges. You can vote on which model produced the better output in a blind duel. Browsing and voting are free. No account is needed to look; signing in only saves your votes and likes.

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